torch-mlir/frontends/pytorch/csrc/builder/func_builder.cpp

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//===- func_builder.cpp ---------------------------------------------------===//
//
// This file is licensed under a pytorch-style license
// See frontends/pytorch/LICENSE for license information.
//
//===----------------------------------------------------------------------===//
#include "func_builder.h"
#include "mlir-c/BuiltinAttributes.h"
#include "mlir-c/BuiltinTypes.h"
#include "mlir-c/Diagnostics.h"
#include "npcomp-c/Types.h"
using namespace torch_mlir;
static MlirOperation createStandardConstant(MlirLocation loc, MlirType type,
MlirAttribute value) {
OperationStateHolder s("std.constant", loc);
MlirNamedAttribute valueAttr = toMlirNamedAttribute("value", value);
mlirOperationStateAddResults(s, 1, &type);
mlirOperationStateAddAttributes(s, 1, &valueAttr);
return s.createOperation();
}
KernelCallBuilder::KernelCallBuilder(MlirContext context, MlirLocation loc,
const std::string &kernelName,
const c10::FunctionSchema &schema)
: context(context), loc(loc), state("torch.kernel_call", loc),
schema(schema) {
(void)this->context; // Preserve for future.
MlirNamedAttribute kernelNameAttr = toMlirNamedAttribute(
"kernelName",
mlirStringAttrGet(
context, mlirStringRefCreate(kernelName.data(), kernelName.size())));
mlirOperationStateAddAttributes(state, 1, &kernelNameAttr);
addSchemaAttrs();
}
void KernelCallBuilder::addSchemaAttrs() {
// Map the op schema to the kernel_call attributes:
// sigArgTypes
// sigRetTypes
// sigIsVararg
// sigIsVarret
// sigIsMutable
std::vector<MlirNamedAttribute> attrs;
attrs.push_back(toMlirNamedAttribute(
"sigIsMutable", mlirBoolAttrGet(context, schema.is_mutable())));
attrs.push_back(toMlirNamedAttribute(
"sigIsVararg", mlirBoolAttrGet(context, schema.is_vararg())));
attrs.push_back(toMlirNamedAttribute(
"sigIsVarret", mlirBoolAttrGet(context, schema.is_varret())));
// Arg types.
std::vector<MlirAttribute> args;
for (auto &arg : schema.arguments()) {
const std::string &typeStr = arg.type()->str();
args.push_back(mlirStringAttrGet(
context, mlirStringRefCreate(typeStr.data(), typeStr.size())));
}
attrs.push_back(toMlirNamedAttribute(
"sigArgTypes", mlirArrayAttrGet(context, args.size(), args.data())));
// Return types.
std::vector<MlirAttribute> returns;
for (auto &ret : schema.returns()) {
const std::string &typeStr = ret.type()->str();
returns.push_back(mlirStringAttrGet(
context, mlirStringRefCreate(typeStr.data(), typeStr.size())));
}
attrs.push_back(toMlirNamedAttribute(
"sigRetTypes",
mlirArrayAttrGet(context, returns.size(), returns.data())));
// Add attrs to op.
mlirOperationStateAddAttributes(state, attrs.size(), attrs.data());
}
void KernelCallBuilder::addOperand(MlirValue operand) {
mlirOperationStateAddOperands(state, 1, &operand);
}
void KernelCallBuilder::addResultType(MlirType resultType) {
mlirOperationStateAddResults(state, 1, &resultType);
}
MlirOperation KernelCallBuilder::create() { return state.createOperation(); }
std::unique_ptr<FuncBuilder>
FuncBuilder::createFunction(FuncBuilder::Inserter &inserter,
MlirLocation location, const std::string &name,
std::vector<MlirType> &inputTypes) {
auto context = mlirLocationGetContext(location);
// TODO: Create a dedicated API upstream for creating/manipulating func ops.
// (this is fragile and reveals details that are not guaranteed).
std::vector<MlirNamedAttribute> funcAttrs;
funcAttrs.push_back(toMlirNamedAttribute(
"type", mlirTypeAttrGet(mlirFunctionTypeGet(
context, inputTypes.size(), inputTypes.data(),
/*numResults=*/0, /*results=*/nullptr))));
funcAttrs.push_back(toMlirNamedAttribute(
"sym_name", mlirStringAttrGet(
context, mlirStringRefCreate(name.data(), name.size()))));
MlirOperationState state =
mlirOperationStateGet(toMlirStringRef("func"), location);
mlirOperationStateAddAttributes(&state, funcAttrs.size(), funcAttrs.data());
{
// Don't access these once ownership transferred.
MlirRegion newBodyRegion = mlirRegionCreate();
MlirBlock newEntryBlock =
mlirBlockCreate(inputTypes.size(), inputTypes.data());
mlirRegionInsertOwnedBlockAfter(newBodyRegion, {nullptr}, newEntryBlock);
mlirOperationStateAddOwnedRegions(&state, 1, &newBodyRegion);
}
// Need to re-lookup the region/block because we relinquished ownership above.
MlirOperation funcOp = mlirOperationCreate(&state);
MlirRegion bodyRegion = mlirOperationGetRegion(funcOp, 0);
MlirBlock entryBlock = mlirRegionGetFirstBlock(bodyRegion);
inserter(funcOp);
return std::unique_ptr<FuncBuilder>(new FuncBuilder(
context, funcOp, BlockBuilder(entryBlock, /*returnOp=*/{nullptr}, true)));
}
void FuncBuilder::rewriteFuncReturnTypes(std::vector<MlirType> &resultTypes) {
// Get inputs from current function type.
MlirAttribute funcTypeAttr =
mlirOperationGetAttributeByName(funcOp, toMlirStringRef("type"));
assert(!mlirAttributeIsNull(funcTypeAttr) &&
"function missing 'type' attribute");
assert(mlirAttributeIsAType(funcTypeAttr) &&
"function type is not a TypeAttr");
MlirType funcType = mlirTypeAttrGetValue(funcTypeAttr);
std::vector<MlirType> inputTypes;
for (intptr_t i = 0, e = mlirFunctionTypeGetNumInputs(funcType); i < e; ++i) {
inputTypes.push_back(mlirFunctionTypeGetInput(funcType, i));
}
// Make new function type.
MlirType newFuncType =
mlirFunctionTypeGet(context, inputTypes.size(), inputTypes.data(),
resultTypes.size(), resultTypes.data());
MlirAttribute newFuncTypeAttr = mlirTypeAttrGet(newFuncType);
mlirOperationSetAttributeByName(funcOp, toMlirStringRef("type"),
newFuncTypeAttr);
(void)newFuncTypeAttr;
}
MlirValue FuncBuilder::insertConstantOp(MlirOperation op) {
mlirBlockInsertOwnedOperationAfter(entryBlock.getBlock(), prevConstantOp, op);
prevConstantOp = op;
return mlirOperationGetResult(op, 0);
}
MlirValue FuncBuilder::lookupTensor(at::Tensor tensor) {
for (auto it = tensorValueMap.rbegin(), e = tensorValueMap.rend(); it != e;
++it) {
if (it->first.is_same(tensor))
return it->second;
}
return {nullptr};
}
MlirValue FuncBuilder::getScalarConstant(MlirLocation loc, at::Scalar s) {
// Note that interpreter "scalars" match the Python semantics and are
// represented as one of double or int64_t, with a special tag for whether
// it should be interpreted as a bool.
if (s.isIntegral(/*includeBool=*/false)) {
// TODO: Switch to a basicpy.constant that works properly with signed
// integers and then switch this to a signed integer.
MlirType t = mlirIntegerTypeGet(context, 64);
MlirAttribute value = mlirIntegerAttrGet(t, s.to<int64_t>());
return getGeneralConstant(loc, value);
}
if (s.isFloatingPoint()) {
MlirType t = mlirF64TypeGet(context);
MlirAttribute value = mlirFloatAttrDoubleGet(context, t, s.to<double>());
return getGeneralConstant(loc, value);
}
if (s.isBoolean()) {
return getBoolConstant(loc, s.to<bool>());
}
// TODO: s.isComplex()
throw std::invalid_argument("TODO: Scalar of unknown kind");
}
MlirValue FuncBuilder::getBoolConstant(MlirLocation loc, bool v) {
MlirAttribute value = mlirBoolAttrGet(context, v);
return getGeneralConstant(loc, value);
}
MlirValue FuncBuilder::getNoneConstant(MlirLocation loc) {
OperationStateHolder state{"basicpy.singleton", loc};
MlirType noneType = npcompNoneTypeGet(context);
mlirOperationStateAddResults(state, 1, &noneType);
MlirOperation op = state.createOperation();
return insertConstantOp(op);
}
MlirValue FuncBuilder::getGeneralConstant(MlirLocation loc,
MlirAttribute value) {
MlirType valueType = mlirAttributeGetType(value);
MlirOperation constOp = createStandardConstant(loc, valueType, value);
MlirValue constValue = insertConstantOp(constOp);
return constValue;
}
MlirValue FuncBuilder::buildList(MlirLocation loc,
std::vector<MlirValue> &elements) {
MlirType resultType = npcompListTypeGet(context);
OperationStateHolder state{"basicpy.build_list", loc};
mlirOperationStateAddResults(state, 1, &resultType);
mlirOperationStateAddOperands(state, elements.size(), elements.data());
MlirOperation op = state.createOperation();
entryBlock.insertBeforeTerminator(op);
return mlirOperationGetResult(op, 0);
}